Adaptive Optimizations for Surveillance Sensor Network Longevity

被引:0
|
作者
Brooks, R. R. [1 ,2 ]
Siddulugari, Hemanth [1 ,2 ]
机构
[1] Clemson Univ, Holcombe Dept Elect & Comp Engn, Clemson, SC USA
[2] Clemson Univ, Holcombe Dept Elect & Comp Engn, Clemson, SC 29634 USA
来源
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS | 2009年 / 5卷 / 02期
关键词
Sensor Network; Power Conservation; Distributed Adaptation; Surveillance; TRACKING;
D O I
10.1080/15501320601062189
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Sensor networks are typically wireless networks composed of resource-constrained battery powered devices. In this paper, we present a criterion for determining whether or not a surveillance sensor network is viable. We use this criterion to compare methods for extending the effective lifetime of the sensor network. The life extension methods we consider are local adaptations that reduce the energy drain on individual nodes. They are communications range management, node repositioning, and data agreement. Simulations of a surveillance scenario quantify the utility of these methods. Our results indicate that data agreement provides the most improvement in network longevity, and communications range management is also useful. Repositioning nodes to reduce the power needed for communications is dependent on the amount of attenuation experienced by the node's communications signal and the volume of traffic between nodes. When these factors are considered, node repositioning is an effective strategy for network life extension. Synergies between the energy conservation approaches are also explored.
引用
收藏
页码:158 / 184
页数:27
相关论文
共 50 条
  • [41] VIGILANT: "Situation-Aware" Quality of Information Interest Groups for Wireless Sensor Network Surveillance Applications
    Ghataoura, D. S.
    Mitchell, J. E.
    Matich, G. E.
    UNMANNED-UNATTENDED SENSORS AND SENSOR NETWORKS VII, 2010, 7833
  • [42] Constrained Bayesian optimization and spatio-temporal surveillance for sensor network design in the presence of measurement errors
    Chen, Junzhuo
    Aral, Mustafa M.
    Kim, Seong-Hee
    Park, Chuljin
    Xie, Yao
    ENGINEERING OPTIMIZATION, 2023, 55 (03) : 510 - 525
  • [43] ROCKNET: SELF-ORGANIZING WIRELESS SENSOR NETWORK FOR ROCKFALL SURVEILLANCE AND REAL-TIME WARNING
    Schneider, H. R.
    Quinteros, S.
    GEOTECHNICAL ENGINEERING FOR DISASTER MITIGATION AND REHABILITATION 2011/GEOTECHNICAL AND HIGHWAY ENGINEERING - PRACTICAL APPLICATIONS, CHALLENGES AND OPPORTUNITIES, 2011, : 233 - 240
  • [44] Multi-Sensor Surveillance System Based on Integrated Video Analytics
    Purohit, Manoj
    Singh, Manvendra
    Yadav, Saralesh
    Singh, Adarsh Kumar
    Kumar, Ajay
    Kaushik, Brajesh Kumar
    IEEE SENSORS JOURNAL, 2022, 22 (11) : 10207 - 10222
  • [45] Adaptive human sensor model in sensor networks
    Kaupp, T
    Makarenko, A
    Ramos, F
    Upcroft, B
    Williams, S
    Durrant-Whyte, H
    2005 7TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), VOLS 1 AND 2, 2005, : 748 - 755
  • [46] Extracting human behaviors with infrared sensor network
    Honda, Seiichi
    Fukui, Ken-ichi
    Moriyama, Koichi
    Kurihara, Satoshi
    Numao, Masayuki
    INSS 07: PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON NETWORKED SENSING SYSTEMS, 2007, : 122 - +
  • [47] Wireless -sensor -network -based target localization: A semidefinite relaxation approach with adaptive threshold correction
    Tian, Xin
    Wei, Guoliang
    Wang, Licheng
    Zhou, Jun
    NEUROCOMPUTING, 2020, 405 : 229 - 238
  • [48] Adaptive Multi Path Routing Protocol for Heterogeneous Multi-Hop Wireless Sensor Network
    Yang, Hanhua
    ADVANCES IN ENERGY SCIENCE AND TECHNOLOGY, PTS 1-4, 2013, 291-294 : 2532 - 2536
  • [49] Energy Adaptive and Max-Min based BFS Model for Route Optimization in Sensor Network
    Juneja K.
    Recent Advances in Computer Science and Communications, 2021, 14 (09): : 2934 - 2947
  • [50] Ensured Continuous Surveillance Despite Sensor Transition Using Control Barrier Functions
    Guerrero-Bonilla, Luis
    Nieto-Granda, Carlos
    Egerstedt, Magnus
    ROBOTICS RESEARCH, ISRR 2022, 2023, 27 : 404 - 419